Helvia.ai was recently featured in Startupper MAG (#68), one of Greece’s leading entrepreneurship and innovation publications. In the interview, our co-founders Stavros Vassos and Dimitris Balaouras discussed the current state of Artificial Intelligence, the myths around an “AI bubble,” and why the real opportunity lies not in hype—but in digital labor powered by AI Agents.

Below, we’re sharing the key insights from that conversation, translated and adapted for our global audience.

AI Bubble or AI Boom?

The excitement around AI is undeniable—but so is the growing skepticism. Are we heading toward another tech bubble, or are we witnessing a genuine transformation?

According to Helvia.ai, the answer depends on which narrative you focus on.

There is indeed a level of hype, especially around AGI (Artificial General Intelligence)—the idea that machines will soon think and learn like humans. This narrative often comes with inflated promises that don’t reflect today’s technological reality. That’s where the perception of an “AI bubble” comes from.

However, there’s a second, far more grounded narrative: digital labor.

AI Agents are already operating in real production environments. They automate tasks, improve productivity, reduce operational costs, and integrate directly into business workflows. This is not a future vision—it’s happening now. This is the real AI boom.

For businesses—especially in markets like Greece—this shift represents a major opportunity. Companies that move beyond hype and adopt AI pragmatically can gain a significant competitive advantage, even against much larger organizations.

Why Companies Trust Helvia.ai

Many of Helvia.ai’s clients come with one of two challenges:

  • They have specific, high-value use cases but lack the in-house expertise to implement them.
  • They’ve already experimented with AI pilots that never made it to production.

What they find at Helvia.ai is not promises of “magic AI,” but real, production-ready digital labor.

Helvia works as a long-term partner, not just a technology vendor—co-designing solutions, implementing them, and continuously improving them based on real usage.

This approach is built on three core pillars:

  1. Value-first solution design
    Clear scope, measurable KPIs, risk assessment, guardrails, and a realistic rollout plan from day one.
  2. A production-grade AI Agent Platform
    The Helvia.ai Agent Platform includes built-in capabilities such as testing, versioning, logging, evaluation, integrations, and monitoring. This allows teams to focus on where value is created—process mapping and workflow integration—rather than rebuilding infrastructure for every project.
  3. Clear boundaries and governance
    Agents are designed with explicit rules: when to respond, when to ask for clarification, and when to escalate to a human. This is critical in real business environments where operational risk matters.

All agents are continuously monitored in real conversations after go-live, allowing teams to identify failures early and apply targeted improvements.

What’s Next: Helvia.ai Agent Platform 6

Helvia.ai is currently finalizing Helvia.ai Agent Platform 6, scheduled to launch in early 2026.

This new version marks a major step forward in how AI Agents are designed, managed, and optimized, built around two core components:

  • Designer - A powerful environment for building agentic workflows that combine multiple Large Language Model calls, enabling more intelligent, flexible, and robust agent behavior.
  • Observatory - A comprehensive analytics and insights layer that gives organizations full visibility into agent performance and actionable, data-driven insights for continuous optimization.

With a strong focus on usability and UX, the platform gives organizations complete control and transparency over their AI ecosystem.

Why So Many AI Projects Never Reach Production

Despite widespread experimentation, many AI initiatives never make it beyond demos.

The most common reasons?

  • Lack of a clear business use case
  • Unrealistic expectations about current AI capabilities
  • A tech-first mindset instead of a value-first approach
  • Underestimating integration complexity with existing systems
  • Ignoring organizational culture and adoption
  • Treating AI Agents as “just prompts” rather than fully governed, monitored, and owned components of real workflows

Without proper governance, monitoring, and ownership, projects stall before delivering impact.

Practical Advice for Companies Starting with AI Agents

For organizations beginning their AI journey today, Helvia.ai offers clear guidance:

  • Choose partners who know how to take AI to real production, not just demos.
  • Start with clear, well-defined use cases and KPIs from the beginning.
  • Move iteratively—from pilot to scale—rather than attempting risky, large leaps.
  • Don’t be afraid to start simple. A small, focused agent can evolve into something much more powerful through real usage and continuous improvement.
  • Invest early in data quality and production integration.
  • Aim for small, consecutive wins, not one big bet.

The future belongs to the AI-native enterprise—and the encouraging news is that this future is more accessible than ever, even for small and mid-sized companies.

As Featured in Startupper MAG

This interview was originally published in Startupper MAG, Issue #68, highlighting Helvia.ai’s perspective on AI Agents, digital labor, and the practical path from experimentation to real business value.

We’d like to thank the Startupper MAG editorial team for the conversation and the opportunity to share our vision.

If you’d like to learn more about how Helvia.ai helps organizations turn AI into real digital labor, feel free to get in touch.